8-parameter affine mode

ABSTRACT

A method of video processing includes deriving, for a current block, a set of control point motion vectors; determining a motion prediction model for the current block based on the set of CPMVs; and performing a conversion between the current block and a bitstream representation of the current block using the motion prediction model, the motion prediction model being a 8-parameter affine prediction model.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of International Application No.PCT/IB2019/058022, filed on Sep. 23, 2019 which claims the priority toand benefits of International Application No. PCT/CN2018/107166, filedon Sep. 23, 2018. All of the aforementioned patent applications arehereby incorporated by reference in their entireties.

TECHNICAL FIELD

This patent document relates to video coding techniques, devices andsystems.

BACKGROUND

Motion compensation (MC) is a technique in video processing to predict aframe in a video, given the previous and/or future frames by accountingfor motion of the camera and/or objects in the video. Motioncompensation can be used in the encoding of video data for videocompression.

SUMMARY

This document discloses methods, systems, and devices related to the useof affine motion compensation in video coding and decoding.

In one example aspect,

A method of video processing is disclosed. The method comprising:deriving, for a current block, a set of control point (CP) motionvectors (MV); determining a motion prediction model for the currentblock based on the set of CPMVs; and performing a conversion between thecurrent block and a bitstream representation of the current block usingthe motion prediction model, wherein the motion prediction model is a8-parameter affine prediction model.

In yet another representative aspect, a video processing apparatus isdisclosed. The apparatus comprises a processor configured to implementthe methods described herein.

In yet another representative aspect, the various techniques describedherein may be embodied as a computer program product stored on anon-transitory computer readable media. The computer program productincludes program code for carrying out the methods described herein.

In another example aspect, a video encoder apparatus comprises aprocessor and video processing circuitry configured to implement videocoding methods.

In yet another representative aspect, a video decoder apparatus mayimplement a method as described herein.

In yet another aspect, the described methods may be embodied in the formof processor-executable code and stored on a computer-readable medium.

The details of one or more implementations are set forth in theaccompanying attachments, the drawings, and the description below. Otherfeatures will be apparent from the description and drawings, and fromthe claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an example of sub-block based prediction calculation.

FIG. 2A-2B shows examples of Simplified affine motion model. (a)4-parameter affine model; (b) 6-parameter affine model.

FIG. 3 shows an example of affine motion vector field (MVF) persubblock.

FIGS. 4A-4B show candidates for AF_MERGE mode.

FIG. 5 shows example candidate positions for affine merge mode.

FIG. 6 shows an example of a Coding Unit (CU) with four sub-blocks (A-D)and its neighbouring blocks (a-d).

FIG. 7 illustrates an example of sub-block based spatio-temporal mergemode implementation.

FIG. 8 illustrates an example of the planar motion vector predictionprocess.

FIG. 9 is a block diagram illustrating an example of the architecturefor a computer system or other control device that can be utilized toimplement various portions of the presently disclosed technology.

FIG. 10 shows a block diagram of an example embodiment of a mobiledevice that can be utilized to implement various portions of thepresently disclosed technology.

FIG. 11 is a flowchart for an example method of visual media processing.

DETAILED DESCRIPTION

The present document provides several techniques that can be embodiedinto digital video encoders and decoders. Section headings are used inthe present document for clarity of understanding and do not limit scopeof the techniques and embodiments disclosed in each section only to thatsection.

In the present document, the term “video processing” may refer to videoencoding, video decoding, video compression or video decompression. Forexample, video compression algorithms may be applied during conversionfrom pixel representation of a video to a corresponding bitstreamrepresentation or vice versa.

1. Summary

This patent document is related to video/image coding technologies.

Specifically, it is related to motion vector prediction in video/imagecoding. It may be applied to the existing video coding standard likeHEVC, or the standard (Versatile Video Coding) to be finalized. It maybe also applicable to future video/image coding standards or video/imagecodec.

2. Introduction

Sub-block based prediction is first introduced into the video codingstandard by HEVC Annex I (3D-HEVC). With sub-block based prediction, ablock, such as a Coding Unit (CU) or a Prediction Unit (PU), is dividedinto several non-overlapped sub-blocks. Different sub-block may beassigned different motion information, such as reference index or MotionVector (MV), and Motion Compensation (MC) is performed individually foreach sub-block. FIG. 1 shows the concept of sub-block based prediction.

To explore the future video coding technologies beyond HEVC, Joint VideoExploration Team (JVET) was founded by VCEG and MPEG jointly in 2015.Since then, many new methods have been adopted by JVET and put into thereference software named Joint Exploration Model (JEM).

In JEM, sub-block based prediction is adopted in several coding tools,such as affine prediction, Alternative temporal motion vector prediction(ATMVP), spatial-temporal motion vector prediction (STMVP),Bi-directional Optical flow (BIO) and Frame-Rate Up Conversion (FRUC).Affine prediction has also been adopted into VVC.

2.1 Affine Prediction

In HEVC, only translation motion model is applied for motioncompensation prediction (MCP). While in the real world, there are manykinds of motion, e.g. zoom in/out, rotation, perspective motions and theother irregular motions. In the VVC, a simplified affine transformmotion compensation prediction is applied. As shown in FIG. 2 , theaffine motion field of the block is described by two (in the 4-parameteraffine model) or three (in the 6-parameter affine model) control pointmotion vectors.

FIG. 2 shows a simplified affine motion model. (a) 4-parameter affinemodel; (b) 6-parameter affine model

The motion vector field (MVF) of a block is described by the followingequation with the 4-parameter affine model

$\begin{matrix}\left\{ \begin{matrix}{{{mv}^{h}\left( {x,y} \right)} = {{\frac{\left( {{mv_{1}^{h}} - {mv_{0}^{h}}} \right)}{w}x} - {\frac{\left( {{mv_{1}^{v}} - {mv_{0}^{v}}} \right)}{w}y} + {mv_{0}^{h}}}} \\{{{mv}^{v}\left( {x,y} \right)} = {{\frac{\left( {{mv_{1}^{v}} - {mv_{0}^{v}}} \right)}{w}x} + {\frac{\left( {{mv_{1}^{h}} - {mv_{0}^{h}}} \right)}{w}y} + {mv}_{0}^{v}}}\end{matrix} \right. & (1)\end{matrix}$and 6-parameter affine model:

$\begin{matrix}\left\{ \begin{matrix}{{{mv}^{h}\left( {x,y} \right)} = {{\frac{\left( {{mv_{1}^{h}} - {mv_{0}^{h}}} \right)}{w}x} + {\frac{\left( {{mv_{2}^{h}} - {mv_{0}^{h}}} \right)}{h}y} + {mv_{0}^{h}}}} \\{{{mv}^{v}\left( {x,y} \right)} = {{\frac{\left( {{mv_{1}^{v}} - {mv_{0}^{v}}} \right)}{w}x} + {\frac{\left( {{mv_{2}^{v}} - {mv_{0}^{h}}} \right)}{h}y} + {mv}_{0}^{v}}}\end{matrix} \right. & (2)\end{matrix}$where (mv^(h) ₀, mv^(v) ₀) is motion vector of the top-left cornercontrol point, and (mv^(h) ₁, mv^(v) ₁) is motion vector of thetop-right corner control point and (mv^(h) ₂, mv^(v) ₂) is motion vectorof the bottom-left corner control point.

To derive motion vector of each 4×4 sub-block, the motion vector of thecenter sample of each sub-block, as shown in FIG. 3 , is calculatedaccording to Eq. (1) or (2), and rounded to 1/16 fraction accuracy. Thenthe motion compensation interpolation filters are applied to generatethe prediction of each sub-block with derived motion vector.

In VTM, there are two affine motion modes: AF_INTER mode and AF_MERGEmode. For CUs with both width and height larger than 8, AF_INTER modecan be applied. An affine flag in CU level is signalled in the bitstreamto indicate whether AF_INTER mode is used. In this mode, a CP MVPcandidate list with two candidates is constructed.

Affine model can be inherited from spatial neighbouring affine-codedblock such as left, above, above right, left bottom and above leftneighbouring block as shown in FIG. 4A. For example, if the neighbourleft block A in FIG. 4A is coded in affine mode as denoted by A0 in FIG.4B, the Control Point (CP) motion vectors mv₀ ^(N), mv₁ ^(N) and mv₂^(N) of the top left corner, above right corner and left bottom cornerof the neighbouring CU/PU which contains the block A are fetched. Andthe motion vector mv₀ ^(C), mv₁ ^(C) and mv₂ ^(C) (which is only usedfor the 6-parameter affine model) of the top left corner/topright/bottom left on the current CU/PU is calculated based on mv₀ ^(N),mv₁ ^(N) and mv₂ ^(N).

It should be noted that when a CU is coded with affine merge mode, i.e.,in AF_MERGE mode, it gets the first block coded with affine mode fromthe valid neighbour reconstructed blocks. And the selection order forthe candidate block is from left, above, above right, left bottom toabove left as shown FIG. 4A.

The derived CP MVs mv₀ ^(C), mv₁ ^(C) and mv₂ ^(C) of current block canbe used as CP MVs in the affine merge mode. Or they can be used as MVPfor affine inter mode in VVC. It should be noted that for the mergemode, if the current block is coded with affine mode, after deriving CPMVs of current block, the current block may be further split intomultiple sub-blocks and each block will derive its motion informationbased on the derived CP MVs of current block.

2.2 JVET-K0186

Different from VTM wherein only one affine spatial neighboring block maybe used to derive affine motion for a block, in JVET-K0186, it proposesto construct a separate list of affine candidates for the AF_MERGE mode.

1) Insert Inherited Affine Candidates into Candidate List

FIG. 5 shows examples of candidate position for affine merge mode.

Inherited affine candidate means that the candidate is derived from thevalid neighbor reconstructed block coded with affine mode.

As shown in FIG. 5 , the scan order for the candidate block is A₁, B₁,B₀, A₀ and B₂. When a block is selected (e.g., A₁), the two-stepprocedure is applied:

-   -   a) Firstly, use the three corner motion vectors of the CU        covering the block to derive two/three control points of current        block    -   b) Based on the control points of current block to derive        sub-block motion for each sub-block within current block        2) Insert constructed affine candidates

If the number of candidates in affine merge candidate list is less thanMaxNumAffineCand, constructed affine candidates are insert into thecandidate list.

Constructed affine candidate means the candidate is constructed bycombining the neighbor motion information of each control point.

The motion information for the control points is derived firstly fromthe specified spatial neighbors and temporal neighbor shown in FIG. 5 .CPk (k=1, 2, 3, 4) represents the k-th control point. A₀, A₁, A₂, B₀,B₁, B₂ and B₃ are spatial positions for predicting CPk (k=1, 2, 3); T istemporal position for predicting CP4.

The coordinates of CP1, CP2, CP3 and CP4 is (0, 0), (W, 0), (H, 0) and(W, H), respectively, where W and H are the width and height of currentblock.

The motion information of each control point is obtained according tothe following priority order:

-   -   For CP1, the checking priority is B₂→B₃→A₂. B₂ is used if it is        available. Otherwise, if B₂ is unavailable, B₃ is used. If both        B₂ and B₃ are unavailable, A₂ is used. If all the three        candidates are unavailable, the motion information of CP1 cannot        be obtained.    -   For CP2, the checking priority is B1→B0;    -   For CP3, the checking priority is A1→A0;    -   For CP4, T is used.

Secondly, the combinations of controls points are used to construct themotion model.

Motion vectors of three control points are needed to compute thetransform parameters in 6-parameter affine model. The three controlpoints can be selected from one of the following four combinations({CP1, CP2, CP4}, {CP1, CP2, CP3}, {CP2, CP3, CP4}, {CP1, CP3, CP4}).For example, use CP1, CP2 and CP3 control points to construct6-parameter affine motion model, denoted as Affine (CP1, CP2, CP3).

Motion vectors of two control points are needed to compute the transformparameters in 4-parameter affine model. The two control points can beselected from one of the following six combinations ({CP1, CP4}, {CP2,CP3}, {CP1, CP2}, {CP2, CP4}, {CP1, CP3}, {CP3, CP4}). For example, usethe CP1 and CP2 control points to construct 4-parameter affine motionmodel, denoted as Affine (CP1, CP2).

The combinations of constructed affine candidates are inserted into tocandidate list as following order:

-   -   {CP1, CP2, CP3}, {CP1, CP2, CP4}, {CP1, CP3, CP4}, {CP2, CP3,        CP4}, {CP1, CP2}, {CP1, CP3}, {CP2, CP3}, {CP1, CP4}, {CP2,        CP4}, {CP3, CP4}        3) Insert zero motion vectors

If the number of candidates in affine merge candidate list is less thanMaxNumAffineCand, zero motion vectors are insert into the candidatelist, until the list is full.

2.3 ATMVP (Advanced Temporal Motion Vector Prediction)

At the 10th JVET meeting, advanced temporal motion vector prediction(ATMVP) was included in the benchmark set (BMS)-1.0 reference software,which derives multiple motion for sub-blocks of one coding unit (CU)based on the motion information of the collocated blocks from temporalneighboring pictures. Although it improves the efficiency of temporalmotion vector prediction, the following complexity issues are identifiedfor the existing ATMVP design:

The collocated pictures of different ATMVP CUs may not be the same ifmultiple reference pictures are used. This means the motion fields ofmultiple reference pictures need to be fetched.

The motion information of each ATMVP CU is always derived based on 4×4units, resulting in multiple invocations of motion derivation and motioncompensation for each 4×4 sub-block inside one ATMVP CU.

Some further simplifications on ATMVP were proposed and have beenadopted in VTM2.0.

2.3.1 Simplified Collocated Block Derivation with One Fixed CollocatedPicture

In this method, one simplified design is proposed to use the samecollocated picture as in HEVC, which is signaled at the slice header, asthe collocated picture for ATMVP derivation. At the block level, if thereference picture of a neighboring block is different from thiscollocated picture, the MV of the block is scaled using the HEVCtemporal MV scaling method, and the scaled MV is used in ATMVP.

Denote the motion vector used to fetch the motion field in thecollocated picture R_(col) as MV_(col). To minimize the impact due to MVscaling, the MV in the spatial candidate list used to derive MV_(col) isselected in the following way: if the reference picture of a candidateMV is the collocated picture, this MV is selected and used as MV_(col)without any scaling. Otherwise, the MV having a reference pictureclosest to the collocated picture is selected to derive MV_(col) withscaling.

2.3.2 Adaptive ATMVP Sub-Block Size

In this method, it is proposed to support the slice-level adaptation ofthe sub-block size for the ATMVP motion derivation. Specifically, onedefault sub-block size that is used for the ATMVP motion derivation issignaled at sequence level. Additionally, one flag is signaled atslice-level to indicate if the default sub-block size is used for thecurrent slice. If the flag is false, the corresponding ATMVP sub-blocksize is further signaled in the slice header for the slice.

2.4 STMVP (Spatial-Temporal Motion Vector Prediction)

STMVP was proposed and adopted in JEM, but not in VVC yet. In STMVP, themotion vectors of the sub-CUs are derived recursively, following rasterscan order. FIG. 6 . illustrates this concept. Let us consider an 8×8 CUwhich contains four 4×4 sub-CUs A, B, C, and D. The neighbouring 4×4blocks in the current frame are labelled as a, b, c, and d.

The motion derivation for sub-CU A starts by identifying its two spatialneighbours. The first neighbour is the N×N block above sub-CU A (blockc). If this block c is not available or is intra coded the other N×Nblocks above sub-CU A are checked (from left to right, starting at blockc). The second neighbour is a block to the left of the sub-CU A (blockb). If block b is not available or is intra coded other blocks to theleft of sub-CU A are checked (from top to bottom, staring at block b).The motion information obtained from the neighbouring blocks for eachlist is scaled to the first reference frame for a given list. Next,temporal motion vector predictor (TMVP) of sub-block A is derived byfollowing the same procedure of TMVP derivation as specified in HEVC.The motion information of the collocated block at location D is fetchedand scaled accordingly. Finally, after retrieving and scaling the motioninformation, all available motion vectors (up to 3) are averagedseparately for each reference list. The averaged motion vector isassigned as the motion vector of the current sub-CU.

FIG. 6 shows an example of one CU with four sub-blocks (A-D) and itsneighbouring blocks (a-d).

2.5 Non-Sub Block STMVP

In this proposal, non subblock STMVP is proposed as a spatial-temporalmerge mode. This proposed method uses a collocated block, which is thesame as HEVC/JEM (only 1 picture, no temporal vector here). The proposedmethod also checks upper and left spatial position, which position isadjusted in this proposal. Specifically to check neighbouringinter-prediction information, at most two positions is checked for eachabove and left. The exact position of Amid, Afar from above row, Lfarand Lmid from left column (as depicted in FIG. 7 ) is shown below:

Afar: (nPbW*5/2, −1), Amid (nPbW/2, −1)

Lfar: (−1, nPbH*5/2), Lmid (−1, nPbH/2)

An average of motion vectors of above block, left block and a temporalblock is calculated as the same as BMS software implementation. If the 3reference inter-prediction blocks is available, denoted the associatedMVs by (mvLX_A[0], mvLX_A[1]), (mvLX_L[0], mvLX_L[1]) and (mvLX_C[0],mvLX_C[1]), respectively, and the final predictor is denoted by(mvLX[0], mvLX[1]).mvLX[0]=((mvLX_A[0]+mvLX_L[0]+mvLX_C[0])*43)/128mvLX[1]=((mvLX_A[1]+mvLX_L[1]+mvLX_C[1])*43)/128

If only two or one inter-prediction block is available, average of twoor just use one my is used.mvLX[0]=(mvLX_D[0]+mvLX_E[0])/2mvLX[1]=(mvLX_D[1]+mvLX_E[1])/22.6 MV Planar

To generate a smooth fine granularity motion field, FIG. 8 gives a briefdescription of the planar motion vector prediction process.

Planar motion vector prediction is achieved by averaging a horizontaland vertical linear interpolation on 4×4 block basis as follows.P(x,y)=(H×P _(h)(x,y)+W×P _(v)(x,y)+H×W)/(2×H×W)W and H denote the width and the height of the block. (x,y) is thecoordinates of current sub-block relative to the above left cornersub-block. All the distances are denoted by the pixel distances dividedby 4. P(x, y) is the motion vector of current sub-block.

The horizontal prediction P_(h)(x, y) and the vertical predictionP_(v)(x, y) for location (x,y) are calculated as follows:P _(h)(x,y)=(W−1−x)×L(−1,y)+(x+1)×R(W,y)P _(v)(x,y)=(H−1−y)×A(x,−1)+(y+1)×B(x,H)

where L(−1, y) and R(W, y) are the motion vectors of the 4×4 blocks tothe left and right of the current block. A(x,−1) and B(x,H) are themotion vectors of the 4×4 blocks to the above and bottom of the currentblock.

The reference motion information of the left column and above rowneighbour blocks are derived from the spatial neighbour blocks ofcurrent block.

The reference motion information of the right column and bottom rowneighbour blocks are derived as follows.

-   -   Derive the motion information of the bottom right temporal        neighbour 4×4 block    -   Compute the motion vectors of the right column neighbour 4×4        blocks, using the derived motion information of the bottom right        neighbour 4×4 block along with the motion information of the        above right neighbour 4×4 block, as described in Equation 1.    -   Compute the motion vectors of the bottom row neighbour 4×4        blocks, using the derived motion information of the bottom right        neighbour 4×4 block along with the motion information of the        bottom left neighbour 4×4 block, as described in Equation 2.        R(W,y)=((H−y−1)×AR+(y+1)×BR)/H  Equation 1        B(x,H)=((W−x−1)×BL+(x+1)×BR)/W  Equation 2

where AR is the motion vector of the above right spatial neighbour 4×4block, BR is the motion vector of the bottom right temporal neighbour4×4 block, and BL is the motion vector of the bottom left spatialneighbour 4×4 block.

The motion information obtained from the neighbouring blocks for eachlist is scaled to the first reference picture for a given list.

3. Problems

The current design of sub-block based prediction has the followingproblems:

The MV planar mode could bring additional coding gain at the cost ofhigh computational complexity and memory bandwidth. For one aspect, itintroduces sub-block motion which increases bandwidth. For anotheraspect, each sub-block need to derive its own motion.

The non-sub block STMVP design introduced division operations which isundesirable for hardware implementation.

The non-sub block STMVP design is only added as a special mergecandidate. If it could also be utilized for inter mode, additionalcoding gain may be expected.

4. Example Techniques

The detailed inventions below should be considered as examples toexplain general concepts. These inventions should not be interpreted ina narrow way. Furthermore, these inventions can be combined in anymanner. Combination between this invention and other invention is alsoapplicable.

Technique 1: Higher Coding Performance

-   1. The MV planar mode may be replaced by a single set of motion    information assigned to a whole block instead of multiple sets of    motion information assigned for each sub-block.    -   a. In one example, the above neighboring blocks (e.g., AL and AR        in FIG. 8 ) may be utilized to derive 1^(st) set of motion        information located at the center position of current block. The        bottom neighboring blocks (e.g., BL and BR in FIG. 8 ) may be        utilized to derive 2^(nd) set of motion information located at        the center position of current block. The final motion candidate        for the current block is then derived from 1^(st) and 2^(nd) set        of motion information.    -   b. In one example, 6-parameter affine model (e.g., applied to        AL, AR and BL) in FIG. 8 ) may be utilized to derive 1^(st) set        of motion information located at the center position. The 1^(st)        set of motion information and temporal motion information (e.g.,        motion associated with BR in FIG. 8 ) may be jointly utilized to        derive the final motion candidate.    -   c. In one example, some or all of the motion information pair        (AL, AR), (AL, BL), (BL, BR), (AR, BR), (BL, AR) and (AL, BR)        are used to derive several sets of 4-parameter affine model,        which are then further used to derive the motion information        located at the center position. These multiple sets of motion        information may be jointly utilized to derive the final motion        candidate.        -   i. In one example, (AL, AR) and (BL, BR) are used to derive            two sets of 4-parameter affine model.    -   d. In one example, motion information of multiple spatial and        temporal neighboring blocks may be utilized to derive one set of        motion information, e.g., linear combination of all available        motion information (e.g., after potential scaling to the same        reference picture) associated with spatial/temporal neighboring        blocks may be utilized to derive the final motion candidate.-   2. A motion candidate derived jointly from spatial and temporal    motion information may be added to the AMVP candidate list.    -   a. In one example, given a target reference picture (which may        be signaled in the bitstream), the MVs of spatial and temporal        blocks may be firstly scaled to the target reference picture.        The scaled MVs may be jointly used to derive a final motion        vector predictor.    -   b. In one example, the derivation process of using multiple MVs        to form a final MV predictor is defined as a linear function.        -   i. In one example, average of multiple MVs may be defined as            the final MV predictor.        -   ii. Alternatively, unequal weight may be applied to            different MVs to form the final MV predictor.-   3. Multiple motion candidates derived from above methods may be    added to motion candidate lists.    -   a. For each of the multiple motion candidate, different spatial        or temporal block may be utilized.    -   b. In one example, the two or more MV used to generate the        derived motion candidate must refer to the same reference        picture;    -   c. In one example, the two or more MV used to generate the        derived motion candidate must refer to reference pictures in the        same reference list;    -   d. In one example, the two or more MV used to generate the        derived motion candidate must refer to a reference picture with        the same reference index in the same reference list;    -   e. In one example, the two or more MV used to generate the        derived motion candidate may refer to different reference        pictures.        -   i. In one example, they will be scaled to the same reference            picture.        -   ii. In one example, they will be scaled to reference picture            closest to the current picture.-   4. Selection of spatial neighboring blocks in above proposed methods    may be fixed, or be adaptively changed.    -   a. In one example, selection of spatial neighboring blocks may        depend on block size, and/or block shape.    -   b. In one example, selection of spatial neighboring blocks may        depend on coded mode (affine, non-affine, amvp or merge, slice        type, etc. al).    -   c. In one example, selection of spatial neighboring blocks may        depend on inter-prediction direction (L0, L1 or Bi)-   5. It is proposed to use the same collocated picture as used in TMVP    and/or ATMVP design, which is signaled at the slice header, as the    target picture where MVs are scaled to for STMVP derivation.    -   a. At the block level, if the reference picture of a neighboring        block is different from this collocated picture, the MV of the        block is scaled, e.g., using the HEVC temporal MV scaling        method, and the scaled MV is used in STMVP motion derivation        process.    -   b. Alternatively, the target picture is determined by the first        available merge candidate.    -   c. Alternatively, the target picture is determined as the        reference picture closest to the current picture.    -   d. Alternatively, for one reference picture list, the collocated        picture may be used as a target picture for one reference        picture list, and for the other reference picture list, the same        reference picture associated with one of spatial neighboring        block may be chosen.-   6. With above methods, maximum number of candidates to be added to a    candidate list and/or what kind of inserting order to the candidate    list may be pre-defined.    -   a. Alternatively, it may be dependent on coded mode (e.g., AMVP        or merge; affine or non-affine).    -   b. Alternatively, it may be dependent on coded block size/block        shape/slice type.    -   c. It may be signaled in in SPS, PPS, VPS, slice header/tile        header, ect. al.-   7. 8-parameter affine mode is proposed that 4 control points MVs are    required for one affine model.    -   a. In one example, in addition to the three CP used in        6-parameter affine model (e.g., CP0, CP1, and CP2 in FIG. 1 ),        one more CP associated with the bottom-right position of the        current block is further involved.        -   i. In one example, the temporal motion information from one            or multiple temporal neighboring block(s) may be used as a            predictor for the bottom-right CP of the current block.    -   b. In one example, for the AMVP mode, 4 MVDs may be signaled.        Alternatively, furthermore, prediction between these 4 MVDs may        be applied.    -   c. In one example, the CP MV associated with the bottom-right CP        is stored even the motion information used in motion        compensation may be different.

Complexity Reduction

-   8. It is proposed to only access blocks for the sub-block STMVP    and/or non-sub block STMVP or other kinds of motion candidates    located at certain positions.    -   a. In one example, the position of a neighboring block (x,y)        should satisfy that x % M=0 and y % N=0 wherein M and N are two        non-zero integers, such as M=N=8 or 16, 32 or 64.    -   b. In one example, if the top-left sample in one neighboring        block doesn't satisfy the given conditions, the checking of the        motion information associated with this block is skipped.        Therefore, the associated motion information couldn't be added        to the merge candidate list.    -   c. Alternatively, if the top-left sample in one neighboring        block doesn't satisfy the given conditions, the position of this        block may be shifted, truncated or rounded to make sure the        conditions are satisfied. For example, (x, y) may be modified to        ((x/M)*M, (y/N)*N) wherein ‘/’ is the integer division.    -   d. A restricted region size covering all the neighboring blocks        is pre-defined/signaled. In this case, when a neighboring block        calculated by a given offset (OffsetX, OffsetY) is outside the        region, it is marked as unavailable or treated as intra-code        mode. The corresponding motion information could not be utilized        to generate a motion candidate to the candidate list.    -   i. In one example, the region size is defined as one CTB, or        multiple CTBs    -   ii. In one example, the region size is defined as W*H (e.g.,        W=64 and H=64). Alternatively, furthermore, all neighbouring        blocks with coordinator (NAx, NAy) should satisfy at least one        of the following conditions:        NAx>=((Cx/W)*W)  1)        NAx<=((Cx/W)*W)+W.  2)        NAy>=((Cy/H)*H)  3)        NAy<=((Cy/H)*H)+H.  4)        wherein ‘>=’ and/or ‘<=’ in above functions may be replaced by        ‘>’ and/or ‘<’, and function ‘/’ indicates the integer division        operations wherein the fractional part of the division results        is discarded.-   iii. Alternatively, all blocks above the LCU row covering the    current block are marked as unavailable or treated as intra-code    mode. The corresponding motion information could not be utilized to    generate a motion candidate to the candidate list.-   iv. Alternatively, suppose the top-left sample coordinate of the LCU    covering current block by (LX, LY). (LX−NAx) and/or abs(LX−NAx)    and/or (LY−NAy) and/or abs(LY−NAy) should be within a threshold.    -   1. One or multiple thresholds may be predefined. They could be        further dependent on minimum size of CU height/minimum size of        width/LCU size etc., al. For example, (LY-NAy) should be less        than the minimum size of CU height, or (LY−NAy) should be less        than twice of the minimum size of CU height.-   v. The region size or the threshold(s) may be signaled in SPS, PPS,    VPS, slice header/tile header, ect. al.-   vi. In one example, all neighbouring blocks outside the current    slice/tile/other kinds of unit for parallel coding are marked as    unavailable, and the corresponding motion information could not be    utilized to derive a candidate to the candidate list.-   9. Division operations of calculating the average of 2 or 3 or more    motion vectors is replaced by shift operations.    -   a. Average of three MVs:        mvLX[0]=((mvLX_A[0]+mvLX_L[0]+mvLX_C[0])*S+W)>>N        mvLX[1]=((mvLX_A[1]+mvLX_L[1]+mvLX_C[1])*S+W)>>N        -   For example, S=43 W=64 and N=7.    -   b. Average of two MVs:        mvLX[0]=((mvLX_A[0]+mvLX_L[0]+1))>>1        mvLX[1]=((mvLX_A[1]+mvLX_L[1]+1))>>1    -   c. Average of M MVs is calculated as:

${{mvL{X\lbrack 0\rbrack}} = {\left( {{\left( {\sum\limits_{i = 0}^{M - 1}{{mvLXi}\lbrack 0\rbrack}} \right)*S} + O} \right) \gg N}}{{{mvLX}\lbrack 1\rbrack} = {\left( {{\left( {\sum\limits_{i = 0}^{M - 1}{{mvLXi}\lbrack 1\rbrack}} \right)*S} + O} \right) \gg N}}$

-   -   -   wherein S and N may be designed differently for different M.            For example, N can be 7, 8, 9, 10 etc.            -   i. In one example, given N, S is chosen as the number                that S/2{circumflex over ( )}N is closest but smaller                than or equal to 1/M.            -   ii. In one example, given N, S is chosen as the number                that S/2{circumflex over ( )}N is closest but larger                than or equal to 1/M.            -   iii. In one example, if S/2{circumflex over ( )}N is                equal to 1/M, O is chosen as 1<<(N−1).            -   iv. In one example, if S/2{circumflex over ( )}N is                smaller than 1/M, O is chosen to be larger than or equal                to 1<<(N−1).            -   v. In one example, if S/2{circumflex over ( )}N is                larger than 1/M, O is chosen to be smaller than or equal                to 1<<(N−1).

d. Alternatively, average of M MVs is calculated as:

${{mvL{X\lbrack 0\rbrack}} = {{{sign}\left( {\sum\limits_{i = 0}^{M - 1}{{mvLXi}\lbrack 0\rbrack}} \right)*\left( {{{{abs}\left( {\sum\limits_{i = 0}^{M - 1}\lbrack 0\rbrack} \right)}*S} + O} \right)} \gg N}}{{{mvLX}\lbrack 1\rbrack} = {{{sign}\left( {\sum\limits_{i = 0}^{M - 1}{{mvLXi}\lbrack 1\rbrack}} \right)*\left( {{{{abs}\left( {\sum\limits_{i = 0}^{M - 1}\lbrack 1\rbrack} \right)}*S} + O} \right)} \gg N}}$

FIG. 9 is a block diagram illustrating an example of the architecturefor a computer system or other control device 2600 that can be utilizedto implement various portions of the presently disclosed technology. InFIG. 9 , the computer system 2600 includes one or more processors 2605and memory 2610 connected via an interconnect 2625. The interconnect2625 may represent any one or more separate physical buses, point topoint connections, or both, connected by appropriate bridges, adapters,or controllers. The interconnect 2625, therefore, may include, forexample, a system bus, a Peripheral Component Interconnect (PCI) bus, aHyperTransport or industry standard architecture (ISA) bus, a smallcomputer system interface (SCSI) bus, a universal serial bus (USB), IIC(I2C) bus, or an Institute of Electrical and Electronics Engineers(IEEE) standard 674 bus, sometimes referred to as “Firewire.”

The processor(s) 2605 may include central processing units (CPUs) tocontrol the overall operation of, for example, the host computer. Incertain embodiments, the processor(s) 2605 accomplish this by executingsoftware or firmware stored in memory 2610. The processor(s) 2605 maybe, or may include, one or more programmable general-purpose orspecial-purpose microprocessors, digital signal processors (DSPs),programmable controllers, application specific integrated circuits(ASICs), programmable logic devices (PLDs), or the like, or acombination of such devices.

The memory 2610 can be or include the main memory of the computersystem. The memory 2610 represents any suitable form of random accessmemory (RAM), read-only memory (ROM), flash memory, or the like, or acombination of such devices. In use, the memory 2610 may contain, amongother things, a set of machine instructions which, when executed byprocessor 2605, causes the processor 2605 to perform operations toimplement embodiments of the presently disclosed technology.

Also connected to the processor(s) 2605 through the interconnect 2625 isa (optional) network adapter 2615. The network adapter 2615 provides thecomputer system 2600 with the ability to communicate with remotedevices, such as the storage clients, and/or other storage servers, andmay be, for example, an Ethernet adapter or Fiber Channel adapter.

FIG. 10 shows a block diagram of an example embodiment of a mobiledevice 2700 that can be utilized to implement various portions of thepresently disclosed technology. The mobile device 2700 can be a laptop,a smartphone, a tablet, a camcorder, or other types of devices that arecapable of processing videos. The mobile device 2700 includes aprocessor or controller 2701 to process data, and memory 2702 incommunication with the processor 2701 to store and/or buffer data. Forexample, the processor 2701 can include a central processing unit (CPU)or a microcontroller unit (MCU). In some implementations, the processor2701 can include a field-programmable gate-array (FPGA). In someimplementations, the mobile device 2700 includes or is in communicationwith a graphics processing unit (GPU), video processing unit (VPU)and/or wireless communications unit for various visual and/orcommunications data processing functions of the smartphone device. Forexample, the memory 2702 can include and store processor-executablecode, which when executed by the processor 2701, configures the mobiledevice 2700 to perform various operations, e.g., such as receivinginformation, commands, and/or data, processing information and data, andtransmitting or providing processed information/data to another device,such as an actuator or external display. To support various functions ofthe mobile device 2700, the memory 2702 can store information and data,such as instructions, software, values, images, and other data processedor referenced by the processor 2701. For example, various types ofRandom Access Memory (RAM) devices, Read Only Memory (ROM) devices,Flash Memory devices, and other suitable storage media can be used toimplement storage functions of the memory 2702. In some implementations,the mobile device 2700 includes an input/output (I/O) unit 2703 tointerface the processor 2701 and/or memory 2702 to other modules, unitsor devices. For example, the I/O unit 2703 can interface the processor2701 and memory 2702 with to utilize various types of wirelessinterfaces compatible with typical data communication standards, e.g.,such as between the one or more computers in the cloud and the userdevice. In some implementations, the mobile device 2700 can interfacewith other devices using a wired connection via the I/O unit 2703. Themobile device 2700 can also interface with other external interfaces,such as data storage, and/or visual or audio display devices 2704, toretrieve and transfer data and information that can be processed by theprocessor, stored in the memory, or exhibited on an output unit of adisplay device 2704 or an external device. For example, the displaydevice 2704 can display a video frame modified based on the MVPs inaccordance with the disclosed technology.

FIG. 11 shows a flowchart for a method 1100 of video processing. Themethod 1100 includes deriving (1102), for a current block, a set ofcontrol point (CP) motion vectors (MV). The method further includesdetermining (1104) a motion prediction model for the current block basedon the set of CPMVs. The method includes performing (1106) a conversionbetween the current block and a bitstream representation of the currentblock using the motion prediction model, wherein the motion predictionmodel is a 8-parameter affine prediction model.

In another example aspect, another method (the “AMVP method”) of videocoding is disclosed. The AMVP method includes determining, for a currentblock, an advanced motion vector prediction (AMVP) list, and performingconversion between the current block and a bitstream representation ofthe current block by determining a motion vector using the AMVP list.the AMVP list uses spatial and temporal motion information.

In yet another example aspect, another method (8-parameter affinemethod) of video coding is disclosed. The method includes performingconversion between the current block and a bitstream representation ofthe current block using an 8-parameter affine mode that uses 4 controlpoint (CP) motion vectors (MV). The CPs are used based on a codingcondition of the current block.

Various embodiments and techniques disclosed in the present document canbe described in the following listing of examples.

1. A method of video processing, comprising: deriving, for a currentblock, a set of control point (CP) motion vectors (MV); determining amotion prediction model for the current block based on the set of CPMVs;and performing a conversion between the current block and a bitstreamrepresentation of the current block using the motion prediction model,wherein the motion prediction model is a 8-parameter affine predictionmodel.

2. The method of example 1, wherein the set of CPMVs comprises fourCPMVs which are respectively associated with top-left, top-right,bottom-left and bottom-right corners of the current block.

3. The method of example 2, wherein the CPMV associated with thebottom-right corner of the current block is derived from one or moretemporal neighboring blocks of the current block.

4. The method of example 2 or 3, wherein each of the CPMVs respectivelyassociated with the top-left, top-right, and bottom-left corners of thecurrent block is derived from one or more spatial neighboring blocks ofthe current block.

5. The method of any one of examples 1-4, wherein in an advanced motionvector prediction (AMVP) mode, four motion vector differences (MVD)which are associated with the four CPMVs respectively are signaled.

6. The method of example 5, wherein a prediction can be applied betweenthe four MVDs.

7. The method of example 2 or 3, wherein the CPMV associated with thebottom-right corner of the current block is stored even if it isdifferent from the motion information used in a motion compensation forthe bottom-right corner.

8. The method of any one of examples 1-7, wherein the conversioncomprises at least one of encoding the current block into the bitstreamrepresentation of the current block and decoding the current block fromthe bitstream representation of the current block.

9. A video processing apparatus comprising a processor configured toimplement the method of any one of examples 1 to 8.

10. A computer program product stored on a non-transitory computerreadable media, the computer program product including program code forcarrying out the method in any one of examples 1 to 8.

With respect to the method 1100, the AMVP method and the 8-parameteraffine mode method, additional examples of implementations andembodiments are provided in the Techniques described in Section 4 andthe listing of claim attached herewith, which forms a part of thedescription.

In another example aspect, a video encoder apparatus comprises aprocessor and video processing circuitry configured to implement videocoding methods.

In yet another representative aspect, a video decoder apparatus mayimplement a method as described herein.

In yet another aspect, the described methods may be embodied in the formof processor-executable code and stored on a computer-readable medium.

The disclosed and other embodiments, modules and the functionaloperations described in this document can be implemented in digitalelectronic circuitry, or in computer software, firmware, or hardware,including the structures disclosed in this document and their structuralequivalents, or in combinations of one or more of them. The disclosedand other embodiments can be implemented as one or more computer programproducts, i.e., one or more modules of computer program instructionsencoded on a computer readable medium for execution by, or to controlthe operation of, data processing apparatus. The computer readablemedium can be a machine-readable storage device, a machine-readablestorage substrate, a memory device, a composition of matter effecting amachine-readable propagated signal, or a combination of one or morethem. The term “data processing apparatus” encompasses all apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, or multiple processors or computers.The apparatus can include, in addition to hardware, code that creates anexecution environment for the computer program in question, e.g., codethat constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, or a combination of one or moreof them. A propagated signal is an artificially generated signal, e.g.,a machine-generated electrical, optical, or electromagnetic signal, thatis generated to encode information for transmission to suitable receiverapparatus.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, and it can bedeployed in any form, including as a stand-alone program or as a module,component, subroutine, or other unit suitable for use in a computingenvironment. A computer program does not necessarily correspond to afile in a file system. A program can be stored in a portion of a filethat holds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

The processes and logic flows described in this document can beperformed by one or more programmable processors executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random-access memory or both. The essential elements of a computer area processor for performing instructions and one or more memory devicesfor storing instructions and data. Generally, a computer will alsoinclude, or be operatively coupled to receive data from or transfer datato, or both, one or more mass storage devices for storing data, e.g.,magnetic, magneto optical disks, or optical disks. However, a computerneed not have such devices. Computer readable media suitable for storingcomputer program instructions and data include all forms of non-volatilememory, media and memory devices, including by way of examplesemiconductor memory devices, e.g., EPROM, EEPROM, and flash memorydevices; magnetic disks, e.g., internal hard disks or removable disks;magneto optical disks; and CD ROM and DVD-ROM disks. The processor andthe memory can be supplemented by, or incorporated in, special purposelogic circuitry.

While this patent document contains many specifics, these should not beconstrued as limitations on the scope of any invention or of what may beclaimed, but rather as descriptions of features that may be specific toparticular embodiments of particular inventions. Certain features thatare described in this patent document in the context of separateembodiments can also be implemented in combination in a singleembodiment. Conversely, various features that are described in thecontext of a single embodiment can also be implemented in multipleembodiments separately or in any suitable subcombination. Moreover,although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. Moreover, the separation of various system components in theembodiments described in this patent document should not be understoodas requiring such separation in all embodiments.

Only a few implementations and examples are described and otherimplementations, enhancements and variations can be made based on whatis described and illustrated in this patent document.

The invention claimed is:
 1. A method of video processing, comprising:deriving, for a current block of a video, a set of control point (CP)motion vectors (MV); determining a motion prediction model for thecurrent block based on the set of CPMVs; and performing a conversionbetween the current block and a bitstream of the video using the motionprediction model, wherein the motion prediction model is an 8-parameteraffine prediction model, and wherein the set of CPMVs comprises fourCPMVs which are respectively associated with top-left, top-right,bottom-left and bottom-right corners of the current block.
 2. The methodof claim 1, wherein the CPMV associated with the bottom-right corner ofthe current block is derived from one or more temporal neighboringblocks of the current block.
 3. The method of claim 1, wherein each ofthe CPMVs respectively associated with the top-left, top-right, andbottom-left corners of the current block is derived from one or morespatial neighboring blocks of the current block.
 4. The method of claim1, wherein in an advanced motion vector prediction (AMVP) mode, fourmotion vector differences (MVD) which are associated with the four CPMVsrespectively are signaled.
 5. The method of claim 4, wherein aprediction can be applied between the four MVDs.
 6. The method of claim1, wherein the CPMV associated with the bottom-right corner of thecurrent block is stored even if it is different from the motioninformation used in a motion compensation for the bottom-right corner.7. The method of claim 1, wherein the conversion includes encoding thecurrent block into the bitstream.
 8. The method of claim 1, wherein theconversion includes decoding the current block from the bitstream.
 9. Anapparatus for processing video data comprising a processor and anon-transitory memory with instructions thereon, wherein theinstructions upon execution by the processor, cause the processor to:derive, for a current block of a video, a set of control point (CP)motion vectors (MV); determine a motion prediction model for the currentblock based on the set of CPMVs; and perform a conversion between thecurrent block and a bitstream of the video using the motion predictionmodel, wherein the motion prediction model is an 8-parameter affineprediction model, and wherein the set of CPMVs comprises four CPMVswhich are respectively associated with top-left, top-right, bottom-leftand bottom-right corners of the current block.
 10. The apparatus ofclaim 9, wherein the CPMV associated with the bottom-right corner of thecurrent block is derived from one or more temporal neighboring blocks ofthe current block.
 11. The apparatus of claim 9, wherein each of theCPMVs respectively associated with the top-left, top-right, andbottom-left corners of the current block is derived from one or morespatial neighboring blocks of the current block.
 12. The apparatus ofclaim 9, wherein in an advanced motion vector prediction (AMVP) mode,four motion vector differences (MVD) which are associated with the fourCPMVs respectively are signaled.
 13. The apparatus of claim 12, whereina prediction can be applied between the four MVDs.
 14. The apparatus ofclaim 9, wherein the CPMV associated with the bottom-right corner of thecurrent block is stored even if it is different from the motioninformation used in a motion compensation for the bottom-right corner.15. The apparatus of claim 9, wherein the conversion includes encodingthe current block into the bitstream.
 16. The apparatus of claim 9,wherein the conversion includes decoding the current block from thebitstream.
 17. A non-transitory computer-readable recording mediumstoring a bitstream of a video which is generated by a method performedby a video processing apparatus, wherein the method comprises: deriving,for a current block of the video, a set of control point (CP) motionvectors (MV); determining a motion prediction model for the currentblock based on the set of CPMVs; and generating the bitstream from thecurrent block using the motion prediction model, wherein the motionprediction model is an 8-parameter affine prediction model, and whereinthe set of CPMVs comprises four CPMVs which are respectively associatedwith top-left, top-right, bottom-left and bottom-right corners of thecurrent block.
 18. The non-transitory computer-readable recording mediumof claim 17, wherein the CPMV associated with the bottom-right corner ofthe current block is derived from one or more temporal neighboringblocks of the current block.
 19. The non-transitory computer-readablerecording medium of claim 17, wherein each of the CPMVs respectivelyassociated with the top-left, top-right, and bottom-left corners of thecurrent block is derived from one or more spatial neighboring blocks ofthe current block.
 20. The non-transitory computer-readable recordingmedium of claim 17, wherein in an advanced motion vector prediction(AMVP) mode, four motion vector differences (MVD) which are associatedwith the four CPMVs respectively are signaled.